KiWi: A key-value map for scalable real-time analytics

Dmitry Basin, Edward Bortnikov, Anastasia Braginsky, Guy Golan-Gueta, Eshcar Hillel, Idit Keidar, Moshe Sulamy

Research output: Contribution to journalArticlepeer-review


We present KiWi, the first atomic KV-map to efficiently support simultaneous large scans and real-time access. The key to achieving this is treating scans as first class citizens and organizing the data structure around them. KiWi provides wait-free scans, whereas its put operations are lightweight and lock-free. It optimizes memory management jointly with data structure access. We implement KiWi and compare it to state-of-the-art solutions. Compared to other KV-maps providing atomic scans, KiWi performs either long scans or concurrent puts an order of magnitude faster. Its scans are twice as fast as non-atomic ones implemented via iterators in the Java skiplist.

Original languageEnglish
Article number16
JournalACM Transactions on Parallel Computing
Issue number3
StatePublished - Aug 2020


  • Concurrent data structures
  • key-value maps


Dive into the research topics of 'KiWi: A key-value map for scalable real-time analytics'. Together they form a unique fingerprint.

Cite this